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eess.IV2025
Imaging Transformer for MRI Denoising: a Scalable Model Architecture that enables SNR << 1 Imaging
Hui Xue, Sarah M. Hooper, Rhodri H. Davies +9
Purpose: To propose a flexible and scalable imaging transformer (IT) architecture with three attention modules for multi-dimensional imaging data and apply it to MRI denoising with…
eess.IV2024★ 1 cited
Imaging transformer for MRI denoising with the SNR unit training: enabling generalization across field-strengths, imaging contrasts, and anatomy
Hui Xue, Sarah Hooper, Azaan Rehman +11
The ability to recover MRI signal from noise is key to achieve fast acquisition, accurate quantification, and high image quality. Past work has shown convolutional neural networks…
eess.IV2024★ 5 cited
Bayesian Uncertainty Estimation by Hamiltonian Monte Carlo: Applications to Cardiac MRI Segmentation
Yidong Zhao, Joao Tourais, Iain Pierce +5
Deep learning (DL)-based methods have achieved state-of-the-art performance for many medical image segmentation tasks. Nevertheless, recent studies show that deep neural networks (…